Evidence map›Paper›PMID 24066147›Full record

ArticlePloS one2013

A novel electronic data collection system for large-scale surveys of neglected tropical diseases.

Jonathan D King, Joy Buolamwini, Elizabeth A Cromwell, Andrew Panfel, Tesfaye Teferi, Mulat Zerihun, Berhanu Melak, Jessica Watson, Zerihun Tadesse, Danielle Vienneau and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 2 pooled it
19.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 2 syntheses or guidelines pooled it, 114 citations in OpenAlex.

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  11. Scoping review of health information technology usability methods leveraged in Africa.Journal of the American Medical Informatics Association : JAMIA · 2023
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 4 countries.

Jonathan D KingThe Carter Center, Atlanta, Georgia, United States of America ; Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland ; University of Basel, Basel, Switzerland.
Joy Buolamwini
Elizabeth A Cromwell
Andrew Panfel
Tesfaye Teferi
Mulat Zerihun
Berhanu Melak
Jessica Watson
Zerihun Tadesse
Danielle Vienneau
Jeremiah Ngondi
Jürg Utzinger
Peter Odermatt
Paul M Emerson
The Carter Center · ETCarter Center · USGeorgia Institute of Technology · USUniversity of Basel · CHUniversity of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLarge cross-sectional household surveys are common for measuring indicators of neglected tropical disease control programs. As an alternative to standard paper-based data collection, we utilized novel paperless technology to collect data electronically from over 12,000 households in Ethiopia. METHODOLOGY: We conducted a needs assessment to design an Android-based electronic data collection and management system. We then evaluated the system by reporting results of a pilot trial and from comparisons of two, large-scale surveys; one with traditional paper questionnaires and the other with tablet computers, including accuracy, person-time days, and costs incurred. PRINCIPLE

findingsThe electronic data collection system met core functions in household surveys and overcame constraints identified in the needs assessment. Pilot data recorders took 264 (standard deviation (SD) 152 sec) and 260 sec (SD 122 sec) per person registered to complete household surveys using paper and tablets, respectively (P = 0.77). Data recorders felt a lack of connection with the interviewee during the first days using electronic devices, but preferred to collect data electronically in future surveys. Electronic data collection saved time by giving results immediately, obviating the need for double data entry and cross-correcting. The proportion of identified data entry errors in disease classification did not differ between the two data collection methods. Geographic coordinates collected using the tablets were more accurate than coordinates transcribed on a paper form. Costs of the equipment required for electronic data collection was approximately the same cost incurred for data entry of questionnaires, whereas repeated use of the electronic equipment may increase cost savings. CONCLUSIONS/SIGNIFICANCE: Conducting a needs assessment and pilot testing allowed the design to specifically match the functionality required for surveys. Electronic data collection using an Android-based technology was suitable for a large-scale health survey, saved time, provided more accurate geo-coordinates, and was preferred by recorders over standard paper-based questionnaires.

Indexed as

Databases, FactualNeglected DiseasesData CollectionElectronic Health RecordsHumansSurveys and QuestionnairesTropical Climate

Identifiers

PMID24066147
PMCPMC3774718
OpenAlexW2132295896

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.